Journal Club

We will discuss about "Reduced model for female endocrine dynamics: Validation and functional variations." Mathematical Biosciences 358 (2023): 108979. Abstract A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle …

We will discuss about “Transcriptome-wide analysis of cell cycle-dependent bursty gene expression from single-cell RNA-seq data using mechanistic model-based inference”, bioRxiv (2024) Abstract Bursty gene expression is quantified by two intuitive parameters: the burst frequency and the burst size. While these parameters are known to be cell-cycle dependent for some genes, a transcriptome-wide picture remains …

We will discuss about "Anti-Windup Protection Circuits for Biomolecular Integral Controllers", bioRxiv (2023).   Abstract Robust Perfect Adaptation (RPA) is a desired property of biological systems wherein a system’s output perfectly adapts to a steady state, irrespective of a broad class of perturbations. Achieving RPA typically requires the deployment of integral controllers, which continually adjust …

We will discuss about "Phenotypic switching in gene regulatory networks", PNAS (2014).   Abstract Noise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a …

We will discuss about "An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells", ArXiv (2023).   Abstract Detecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology, rhythms in time series (for instance gene expression, eclosion, egg-laying and feeding) datasets tend to …

We will discuss about “Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming”, Cell (2019).   Abstract Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. …

We will discuss about “PenDA, a rank-based method for personalized differential analysis: Application to lung cancer” Plos Computational Biology (2020). Abstract The hopes of precision medicine rely on our capacity to measure various high-throughput genomic information of a patient and to integrate them for personalized diagnosis and adapted treatment. Reaching these ambitious objectives will require …

We will discuss about “Data driven governing equations approximation using deep neural networks” Journal of Computational Physics (2019). Abstract We present a numerical framework for approximating unknown governing equations using observation data and deep neural networks (DNN). In particular, we propose to use residual network (ResNet) as the basic building block for equation approximation. We demonstrate that the ResNet block can be …

In this talk, we discuss the paper "Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe", by Xiaojie Qiu  et.al., Cell Syst. 2020. Abstract  Here, we present Scribe (https://github.com/aristoteleo/Scribe-py), a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe …

In this talk, we discuss the paper, "MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data" by Siyao Liu et.al.  Genome Biology, 2024. Abstract  Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) …

In this talk, we will discuss the paper, "A modified shuffled frog leaping algorithm with inertia weight", by Zhuanzhe Zhao et.al. , Scientific Reports, 2024. Abstract  The shuffled frog leaping algorithm (SFLA) is a promising metaheuristic bionics algorithm, which has been designed by the shuffled complex evolution and the particle swarm optimization (PSO) framework. However, …

In this talk, we discuss the paper "Holimap: an accurate and efficient method for solving stochastic gene network dynamics" by Chen Jia and Ramon Grima, bioRxiv, 2024. Abstract  Gene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently …